ERIC Number: EJ1434886
Record Type: Journal
Publication Date: 2024-Aug
Pages: 51
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0049-1241
EISSN: EISSN-1552-8294
Available Date: N/A
A Bayesian Semi-Parametric Approach for Modeling Memory Decay in Dynamic Social Networks
Sociological Methods & Research, v53 n3 p1201-1251 2024
In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently occurred events may have a stronger influence on current interaction behavior than past events that occurred a long time ago--a phenomenon known as "memory decay". Previous studies either predefined a short-run and long-run memory or fixed a parametric exponential memory decay using a predefined half-life period. In real-life relational event networks, however, it is generally unknown how the influence of past events fades as time goes by. For this reason, it is not recommendable to fix memory decay in an ad-hoc manner, but instead we should learn the shape of memory decay from the observed data. In this paper, a novel semi-parametric approach based on Bayesian Model Averaging is proposed for learning the shape of the memory decay without requiring any parametric assumptions. The method is applied to relational event history data among socio-political actors in India and a comparison with other relational event models based on predefined memory decays is provided.
Descriptors: Bayesian Statistics, Social Networks, Memory, Decision Making, Models, Cognitive Ability, Behavior Patterns, Foreign Countries, Political Attitudes, Network Analysis, Retention (Psychology), News Reporting, Computational Linguistics, Goodness of Fit
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: India
Grant or Contract Numbers: N/A
Data File: URL: https://doi-org.bibliotheek.ehb.be/10.17605/OSF.IO/79M6H
Author Affiliations: N/A